During ObjectNav transfer, we found it beneficial to sample a long-term goal with a frequency of T=1 steps for PONI (based on val performance). This is unlike prior modular methods [1]}, [2]}, [3]} which learn to sample long-term goals with T=25 steps. For Predict-\(\theta \) and Predict-\(xy\), we found T=25 to work better.
